In patients with suspected acute coronary syndrome high-sensitivity cardiac tropnonin T is used for rapid patient triage. Some acute coronary syndrome patients assigned to the observe zone based on high-sensitivity cardiac troponin T after 1 h require further diagnostic testing. Fast-strain encoded CMR imaging with breathing maneuvers may accelerate diagnostic work-up and identify patients suffering from acute coronary syndrome. Patients presenting with acute chest pain (high-sensitivity cardiac troponin T level 5–52 ng/L) were prospectively enrolled (consecutive sampling, time of recruitment: 09/18–06/19). Fast-strain-encoded imaging was performed within the 1-h timeframe (0 h/1 h algorithm) prior to 2nd high-sensitivity troponin T lab results. Images were acquired at rest as well as after 1-min of hyperventilation followed by a short breath-hold. In 108 patients (59 male; mean age: 57 ± 17y) the mean study time was 17 ± 3 min. An abnormal strain response after the breathing maneuver (persistent/increased/new onset of increased strain rates) correctly identified all 17 patients with a high-sensitivity troponin T dynamic (0 h/1 h algorithm) and explanatory significant coronary lesions, while in 86 patients without serologic or angiographic evidence for severe coronary artery disease the strain response was normal (sensitivity 100%, specificity 94.5%; 5 false positive results). The number of dysfunctional segments (strain > − 10%) proved to be a quantifiable marker for identifying patients with acute coronary syndrome. In patients with suspected acute coronary syndrome and inconclusive initial high-sensitivity troponin T, fast-strain-encoded imaging with a breathing maneuver may safely and rapidly identify patients with acute coronary syndrome, without the need for vasodilators, stress, or contrast agents.
These authors contributed equally: Deborah Siry and Johannes H. Riffel.
Chest pain is one of the most common symptoms in patients presenting to emergency departments (ED). Among various differential diagnoses to be considered, acute coronary syndrome (ACS) is critical because of the potential need for an immediate therapeutic intervention[
According to current guidelines, patients with suspected ACS should undergo an electrocardiogram (ECG) within 10 min, as well as serial biomarker measurements such as high-sensitivity cardiac troponin T (hscTnT)[
Despite its unique tissue characterization capabilities and comprehensive range of quantitative markers, cardiovascular magnetic resonance (CMR) imaging is rarely used in acute clinical settings, mainly due to the associated logistical effort, lengthy protocols, and the frequent need for contrast agents.
Compared to standard CMR protocols, fast Strain-encoded Imaging (fSENC) is an ultrafast (single-heartbeat) method for quantifying myocardial strain, a sensitive marker for abnormal regional and global ventricular function[
Hyperventilation leads to transient reduction of coronary blood flow due to the associated reduction of blood carbon dioxide. Accordingly, hyperventilation has been used for diagnosis of myocardial ischemia[
In a double-blinded study design, patients with acute chest pain suggestive of ACS presenting at our chest pain unit were recruited. Other results of this study cohort have been previously reported[
All patients with an initial hscTnT between 5 and 52 ng/L on admission (0 h/1 h algorithm) underwent a focused fSENC-CMR scan within 1 h after first hscTnT measurement (before second). Patients were closely monitored (ECG, pulse oximetry), and accompanied by a physician during in-hospital transport and during the CMR scan[
Table 1 Inclusion and exclusion criteria of the study[
Inclusion criteria Exclusion criteria Acute chest pain HEART score ≤ 6 Initial hscTnT 5–52 ng/L Signed informed consent Acute ST-elevation myocardial infarction Hemodynamic instability Cardiogenic shock Mechanical complications of MI Systolic heart failure (LVEF < 40%) Life-threatening arrhythmias History of CAD CMR: non-suitable metallic implants CMR: severe claustrophobia
hscTNT high-sensitive cardiac troponin T, LVEF left ventricular ejection fraction, CAD coronary artery disease, MI myocardial infarction, CMR cardiovascular magnetic resonance.
CMR scans were performed in a 1.5 T whole-body CMR scanner (Ingenia CX 1.5 T, Philips Medical Systems, Best, The Netherlands) or, in 16 individuals, in a 3 T whole-body scanner (Ingenia CX 3T, Philips Medical Systems, Best, The Netherlands). The images were displayed in real-time on a computer screen. Patients were in direct contact with the physicians and followed breathing commands through the built-in audio system.
A vector ECG was used for R-wave triggering. Cine images were acquired using a standard cine sequence in 35 acquired phases covering the whole left ventricle from base to apex, as well as in a 2-chamber view and a 4-chamber view (Field of view 140 mm
Additional fSENC images in a 4-chamber view and 3 short axis views were acquired directly after HVBH. (Field of view 100
Graph: Figure 1 Analysis workflow: triage according to change in myocardial deformation before (left) and after hyperventilation: 1 min at 30 brpm followed by a short breath-hold for image acquisition (right). Rule-out = normal contractility at rest and after hyperventilation or improved contractility after hyperventilation; cardiac, non-ACS = generally impaired myocardial deformation; rule-in = increased/persistent or new onset of dysfunctional segments after hyperventilation.
The standard of reference was based on the patient's final clinical diagnosis as determined by staff cardiologists blinded to the CMR results, according to serial hscTnT testing and, if clinically indicated, further diagnostic procedures (coronary angiography, echocardiography, stress ECG, stress CMR or coronary CT). For hscTnT measurements, a 4
If patients were transferred for coronary angiography, significant stenoses were defined as a visual stenosis ≥ 70% of the coronary diameter.
For strain measurements, we used the certified software "MyoStrain" (Myocardial Solutions Inc., Morrisville, NC, USA). The analyses were performed by a MyoStrain-certified examiner blinded to the 2nd hscTnT results.
Endocardial and epicardial borders were contoured manually. Papillary muscles, trabeculae and epicardial fat were excluded from the blood pool.
The circumferential and longitudinal strain values were represented in a color-coded image according to the AHA (American Heart Association) 16-segment model, based on previously established cut-off values[
- Normal myocardial deformation (strain < − 17)
- Mild reduction of myocardial deformation (strain > − 17)
- Severe reduction of myocardial deformation (strain > − 10)
By visual assessment of the fSENC bull's-eye maps, patients were triaged either to 0: non-cardiac, 1: ACS or 2: cardiac, non-ACS causes of acute chest pain. Maps devoid of dysfunctional segments (strain > − 10) after HVBH were considered normal and classified to group 0, whereas patients with persistent, increased, or new onset of regional dysfunction after HVBH were classified to group 1, and patients with global dysfunction not compatible with coronary artery territories were assigned to group 2 (Fig. 1).
Within group 1, the dysfunctional segments were allocated to specific coronary artery territories according to AHA recommendations[
The primary endpoint of this study was defined as the diagnostic accuracy of fSENC and HVBH in predicting ACS (H
All statistical analyses were performed using the computer programs Microsoft Excel (Microsoft, Redmond, CA, USA), SPSS (Version 24, IBM, Armonk, USA) and MedCalc (Version 19.2, MedCalc Software, Ostend, Belgium).
Quantitative data included mean values as well as standard deviation (SD). Receiver Operating Characteristic (ROC) curves and logistic regression curves were compared using the Hanley and McNeil test[
A Kolmogorov–Smirnov test (2-sided) for random distribution, McNemar's test (2-sided) to test fSENC results for deviation from the gold standard and Mann–Whitney U test (2-sided) to detect differences between diagnostic performance of fSENC ± HVBH and hscTnT as well as between time intervals to treatment were performed. Cohen's Kappa coefficient was calculated to evaluate correlation between culprit coronary lesions/severe stenoses as assessed by coronary angiography and fSENC maps. The intraclass correlation coefficient (ICC) (2-sided) was performed to assess interobserver reliability. P-values < 0.05 were regarded as statistically significant.
The study was approved by the local ethics committee (Ethikkommission Medizinische Fakultät Heidelberg (S-483/2018)). All participants provided informed written consent.
We consecutively enrolled a total of 108 patients (49 females, mean age: 57 ± 17y). Of these, 85 were ruled out for a cardiac cause of the chest pain (group 0)—within the rule-out group some patients received additional non-invasive testing as part of routing diagnostic work-up (Echocardiography n = 6, stress-ECG n = 7) with altogether normal results. Another 6 were diagnosed with an underlying cardiac disease (group 2: n = 3 Hypertrophic Cardiomyopathy, n = 1 Dilated Cardiomyopathy, n = 1 Myocarditis, n = 1 Pulmonary Hypertension), whereas 17 were diagnosed with ACS (group 1), including 8 with NSTEMI. Table 2 depicts patient characteristics.
Table 2 Patient characteristics.
Total patient population: 108 Count Mean (± SD) max/min Median IQR Female 49 (45%) Male 59 (55%) Age (years) 57 ± 17 85/20 BMI (kg/m2) 26.6 ± 5.3 52.9/14.8 BP (systolic) (mmHg) 155 ± 20 204/110 HR (bpm) 71 ± 16 133/32 Low 41 Intermediate 67 1 74 (69%) 2 18 (17%) 3 15 (14%) 4 1 (1%) EF (%) 65.4 ± 12.9 96.0/20.5 66.4 16.5 EDV (ml) 92.8 ± 39.4 237.2/40.3 79.1 52.5 ESV (ml) 32.5 ± 21.5 132.6/4.5 26.5 18.8 cvRF 2 5/0 Diabetes 9 (8%) Hypertension 58 (54%) Hypercholesterinemia 34 (31%) Familial predisposition 31 (29%) Non-smoker 62 (57%) 0 ± 1 9/0 Past smoker 32 (30%) 19 ± 15 45/1 Smoker 14 (13%) 25 ± 20 60/3 Chest pain duration (h) (ACS) 15.6 > 24/1 24 21 Chest pain duration (h) (cardiac, non-ACS) 15 > 24/0.5 22 20 Chest pain duration (h) (non-cardiac) 14.9 > 24/1 16 19 hscTnT 0 h (ng/L) 11 ± 8 49/5 hscTnT 1 h (ng/L) 15 ± 21 112/3 Δ hscTnT (kinetics) (ng/L) 5 ± 18 + 93/− 28 Stress ECG 7 (6%) Echocardiography 6 (6%) Standard CMR 1 (1%) CT angiography 1 (1%) Coronary angiography 25 (23%)
max maximum, min minimum, SD standard deviation IQR interquartile range, BMI body mass index, BP blood pressure, HR heart rate, NYHA New York Heart Association, EF ejection fraction, ESV end-systolic volume, EDV end-diastolic volume, cvRF cardiovascular risk factors, py pack years, h hours, ACS acute coronary syndrome, hscTNT high-sensitive cardiac troponin T, ECG electrocardiogram, CMR cardiovascular magnetic resonance, CT computed tomography.
All CMR scans were performed shortly after patient admission with a total mean scan time of 17 ± 3 min (HVBH including instructions: 3 min). In 8 patients, the fSENC images after hyperventilation were not evaluated: 3 of them (group 0 n = 2; group 2 n = 1) were unable to perform the HVBH; in 5 patients (group 1 n = 2; group 0 n = 3), the images were excluded due to low image quality. Therefore, in these 8 patients results were based on the rest images alone.
First, fSENC images obtained at baseline (excluding images after HVBH) were analyzed separately and compared to final clinical diagnosis (standard of reference). With 12 false positive and 3 false negative results, an accuracy of 86.1% was achieved. In a separate analysis, both, baseline and HBHV results were evaluated. This resulted in the detection of an additional 3 patients with ACS who developed changes in myocardial strain, while in 7 other patients, hyperventilation was associated with augmented contraction. Therefore, the addition of the HVBH as a stress test improved the diagnostic performance of fSENC to an accuracy of 95.4% (Table 3).
Table 3 Diagnosis according to fSENC at rest and after HVBH as compared to reference standard.
fSENC + fSENC − fSENC-HV + fSENC-HV − Reference standard ACS (1) 0 12 65 5 71 85 2 0 14 0 15 6 0 + 2
Significant values are in bold.
For quantitative assessment of myocardial strain, the number of dysfunctional segments (strain > − 10) before and after hyperventilation were plotted in a ROC-curve for ACS identification. Patients with non-ischemic heart disease were excluded. The AUC (area under the curve) for the number of dysfunctional segments (ds) at rest was 0.795 (95% CI 0.67–0.92, p < 0.0001), for hscTnT dynamics 0.625 (95% CI 0.41–0.84, p = 0.245), and for the number of dysfunctional segments after hyperventilation 0.842 (95% CI 0.75–0.94, p < 0.0001). The ROC curves for the number of dysfunctional segments at rest and after hyperventilation were significantly different from those for hscTnT dynamics (hscTnT vs. n(ds rest): 95% CI − 0.07 to 0.41, p = 0.158; hscTnT vs. n(ds hv): 95% CI − 0.0004 to 0.44, p < 0.05), however did not differ significantly from each other (95% CI − 0.07 to 0.17, p = 0.446) The AUC of a routine clinical diagnostic work-up with ECG and hscTnT dynamics (1 h–0 h) (AUC ECG + hscTnT: 0.71; 95% CI 0.52–0.90, p < 0.035) was significantly improved when the number of dysfunctional segments (strain > − 10) at rest (AUC ECG + hscTnT + n(ds rest): 0.825; 95% CI 0.70–0.95, p < 0.0001) or after hyperventilation (AUC ECG + hscTnT + n(ds rest) + n(ds hv): 0.857; 95% CI 0.75–0.96, p < 0.0001) was added (Fig. 2B).
Graph: Figure 2 Central illustration of results. (A) Comparison of diagnostic performance of fSENC (at baseline) to hscTnT dynamics (1 h–0 h) and fSENC with HVBH. (B) ROC curves for ACS identification according to quantifiable markers (EF, ECG (ST-wave abnormalities), hscTnT dynamics, number of dysfunctional segments (strain > − 10) at rest and after hyperventilation) and Logistic regression analysis of combined diagnostic methods: (
According to the 0 h/1 h algorithm and clinical findings, 14 patients were ruled in for ACS. In 8 of these 14 patients coronary angiography was performed and thereafter discharged. 74 patients were ruled out for acute myocardial injury in accordance with the 0 h/1 h algorithm. In 4 of the 74 patients, invasive coronary angiography was conducted based on clinical presentation and in 2 of these 4 cases, significant CAD was found.
The remaining 20 patients were assigned to the observe zone after 1 h requiring further diagnostic procedures. In 10 of these patients, coronary angiography was performed revealing significant CAD in 7 cases (Tables 4, 5). Therefore, serial hscTnT measurements alone regarding the 88 patients with a definitive diagnosis after 1 h resulted in a sensitivity of 80%, specificity of 92.3% and an accuracy of 90.3%.
Table 4 Patient classification according to 0 h/1 h algorithm after 1 h with number of patients who underwent coronary angiography.
Rule-in Observe-zone Rule-out 0 h/1 h algorithm 14 20 74 108 Final diagnosis: ACS 8 7 2 17 Final diagnosis: non-cardiac/cardiac, non-ACS 6 13 72 91 Coronary angiography 11 10 4 25
ACS acute coronary syndrome, hscTnT high-sensitive cardiac troponin T.
The combination of fSENC images at rest as well as the images after the HVBH proved to be superior to serial hscTnT measurements (Fig. 2A).
In our patient cohort, 35% of the patients classified to the observe zone were found to have significant CAD and, after full clinical diagnostic evaluation, underwent a therapeutic coronary intervention. Assignment to the observe zone resulted in a significant increase of the mean time-to-treatment (coronary intervention) for ACS patients (54.0 ± 37.6 h) in comparison to patients who were deemed "ruled in" based on hscTnT kinetics (8.1 ± 6.8 h) (95% CI 7.5 h–84.8 h; p < 0.05). fSENC with hyperventilation correctly diagnosed all 20 patients assigned to the observe zone within the 1-h time frame after admission (group 0 n = 13; group 1 n = 7).
The affected coronary artery territories of the 17 patients with ACS were identified visually, using fSENC bull's eye plots according to the AHA 17-segment model (Fig. 3). In 14 of the 17 patients (82%), the culprit coronary lesions and significant stenoses (stenosis ≥ 70% by visual analysis; target vessels for acute intervention) could be correctly identified by fSENC (Table 5).
Graph: Figure 3 Examples of fSENC bull's eye plots before HVBH (above) and after HVBH (below). (A) LAD stenosis with increased dysfunction after HVBH, (B) LCX stenosis with increased dysfunction after HVBH, (D) RCA stenosis with persistent dysfunction after HVBH.
Table 5 Culprit coronary lesions/significant stenoses as identified visually by fSENC bulls-eyes in comparison to coronary angiography results.
Coronary angiography LAD RCA LCX Multiple Total LAD 4 0 0 0 4 RCA 0 1 1 0 2 LCX 0 0 1 0 1 Multiple 2 0 0 8 10 Total 6 1 2 8 17
LAD left anterior descending, RCA right coronary artery, LCX left circumflex.
Cohen's Kappa coefficient for the agreement between fSENC results and the significant coronary lesions according to coronary angiography was strong (0.718; p < 0.05).
In 6 of the 8 patients with multi-vessel disease fSENC showed a combination of LAD (left anterior descending) and RCA (right coronary artery) stenoses. LCX (left circumflex) stenoses > 70% in three-vessel disease (according to coronary angiography/bypass operation) were not well detected by fSENC (Fig. 4).
Graph: Figure 4 Venn diagram of the 8 multi-vessel-disease cases as defined by fSENC (left) and coronary angiography/bypass operation (right).
Fifteen patients were analyzed by a second certified MyoStrain reader blinded to all patient data and previous fSENC results. An ICC of 0.96 and 0.96 was reached for the number of dysfunctional segments (strain > − 10) and the number of segments with a strain > − 17 respectively. These results demonstrate a high level of reproducibility (p < 0.0001).
To our knowledge, this is the first study to assess the diagnostic performance of CMR strain imaging using a standardized breathing maneuver as a replacement for physical or pharmacological stress in patients with acute chest pain. The main findings of our study are:
- The diagnostic performance of a visual evaluation of fSENC maps before and after HVBH was very high (accuracy 95.4%). In all but 5 patients, an ischemic cause of the acute chest pain could be correctly ruled in or ruled out. There were no false negative results.
- The number of dysfunctional segments before and after hyperventilation may serve as a quantifiable surrogate marker for ischemic burden.
- fSENC and HVBH correctly diagnosed all 20 patients within one hour who were assigned to the observe zone according to the hscTnT 0 h/1 h algorithm.
- Additionally, visual analysis of the fSENC images accurately identified the culprit coronary artery and relevant stenoses in most patients.
Our results may have significant clinical implications. As early revascularization in NSTEMI patients improves patient prognosis compared to delayed invasive strategy[
In a recent study we could demonstrate the feasibility of fSENC for diagnostic triage of patients presenting with acute chest pain. Global strain measurements allowed for a safe identification of obstructive CAD—even outperforming ECG and serial hscTnT measurements[
In a recent study conducted by Fischer et al., it could be shown that Oxygenation-Sensitive CMR in combination with hyperventilation allows for the detection of regional myocardial abnormalities related to multi-vessel CAD without the need of medication or contrast agent[
Ochs et al. compared standard adenosine perfusion stress CMR to strain imaging after adenosine infusion as well as strain imaging after hyperventilation. Both, adenosine-strain and HVBH-strain were found to be superior to standard adenosine first-pass perfusion for identification of obstructive CAD[
Of particular importance, patients assigned to the observe zone may have a specific additional benefit from fSENC-CMR and HVBH. In studies on the utility of 1-h protocols, the percentage of patients assigned to the observe-zone varied between 30.5%[
Additionally, of the 20 patients classified to the observe zone, 10 underwent coronary angiography—3 of whom were discharged thereafter. For these 3 patients, invasive diagnostic procedures including radiation could have been avoided based on hyperventilation CMR strain imaging results alone. Thus, this approach could be of particular value in this high-risk patient group.
Furthermore, hyperventilation CMR strain imaging allowed the correct identification of severe stenoses in most cases. There were inaccuracies with lesions in the LCX territory in patients with three-vessel disease, although variations of RCA and LCX territories are well known and could explain the observed discrepancies[
Comparatively, strain analysis tools based on analyzing standard cine images such as feature tracking do not require additional sequences and thus allow for shorter scan times which may be useful and efficient. Strain imaging based on cine images however is hampered by through-plane motion artifacts and partial volume effects[
We excluded patients with history of PCI/bypass operation and with heart failure (EF < 40%). The study population and the final sample size of those deemed to have ACS was modest and confined to a single center, hence no significant difference within the ROC curve analysis could be registered. Findings need to be confirmed in bigger study population. Additionally, absolute values were not analyzed. Furthermore, CAD was determined by visual assessment of the angiographer, and its hemodynamic relevance was not quantified by Fractional Flow Reserve or instantaneous wave-free ratio. No additional standard stress CMR protocols for comparison to our proposed protocol were performed. CMR as well as fSENC and the relevant expertise is currently not available at all clinical institutions. Additionally, fSENC is at this point still comparatively expensive (one scan: circa 385€ vs. one hscTnT test: circa 2,50€).
Our suggested protocol achieved a high diagnostic accuracy, outperforming other clinical markers for ACS identification. This approach may be particularly useful for "troponin observe zone" patients, allowing for a safe, drug-free, and non-invasive assessment of myocardial function.
We thank our technologists Daniel Helm, Melanie Feiner, Vesna Bentele, Miriam Hess and Leonie Siegmund. A special thanks to Noura Nooman Atia, M.Sc. Maximilian Pilz and David Albert who helped with the analysis and patient recruitment.
D.S.: acquisition, analysis, interpretation of data/writing and editing of draft. J.R.: conceptualization, analysis, interpretation of data/editing of draft/supervision. J.S.: interpretation of data. F.A.: interpretation of data/editing of draft. M.O.: interpretation of data. L.W.: acquisition and interpretation of data. E.G.: resources. H.K.: resources. M.F.: conceptualization/analysis, interpretation of data/editing of draft/supervision. All authors have read and approved the final manuscript.
DS was partially supported by the German Heart Foundation.
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
MF is advisor, board member and shareholder of Circle Cardiovascular Imaging Inc., Calgary. MF is listed as one of the original patent holders for the United States Patent 15/483,712: Measuring Oxygenation Changes in Tissue as a Marker for Vascular Function. All other authors declare no competing interests.
• CMR
- Cardiovascular magnetic resonance
• fSENC
- Fast Strain ENCoded
• HVBH
- Hyperventilation breath-hold
• ACS
- Acute coronary syndrome
• hscTnT
- High-sensitive Troponin T
• GCS
- Global circumferential strain
• GLS
- Global longitudinal strain
• ECG
- Electrocardiogram
• BRPM
- Breaths per minute
• ICC
- Intraclass correlation coefficient
• AUC
- Area under the curve
• ED
- Emergency department
• ROC
- Receiver Operating Characteristic
• CAD
- Coronary artery disease
• NSTEMI
- Non-ST-elevation myocardial infarction
• EF
- Ejection fraction
• ESV
- End-systolic volume
• EDV
- End-diastolic volume
• LAD
- Left anterior descending artery
• LCX
- Circumflex artery
• RCA
- Right coronary artery
• DS
- Dysfunctional segments
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
By Deborah Siry; Johannes H. Riffel; Janek Salatzki; Florian Andre; Marco Ochs; Lukas D. Weberling; Evangelos Giannitsis; Hugo A. Katus and Matthias G. Friedrich
Reported by Author; Author; Author; Author; Author; Author; Author; Author; Author